Sam Aberman

Driving the development of Adeline, a cutting-edge AI platform that revolutionizes media sales workflows. By leveraging advanced NLP, machine learning, and optimization techniques, Adeline tackles complex use cases such as Preemption Automation, Promotion Campaign Automation, and Automated Scheduling.
Key Highlights:

AI-Driven Automation: Adeline automates critical sales processes, from RFP ingestion and proposal generation to intelligent media planning. Our AI models, built on… Show more

Driving the development of Adeline, a cutting-edge AI platform that revolutionizes media sales workflows. By leveraging advanced NLP, machine learning, and optimization techniques, Adeline tackles complex use cases such as Preemption Automation, Promotion Campaign Automation, and Automated Scheduling.
Key Highlights:

AI-Driven Automation: Adeline automates critical sales processes, from RFP ingestion and proposal generation to intelligent media planning. Our AI models, built on state-of-the-art architectures like Anthropic's Claude, combine deep domain expertise with machine learning to drive efficiency and effectiveness.
Seamless Integration: Designed to integrate seamlessly with Operative's tech stack, Adeline delivers a unified user experience across the sales lifecycle. By leveraging our OMS, inventory management, and reporting tools, Adeline provides end-to-end workflow automation.
Scalable Cloud Architecture: Adeline's microservices-based, serverless architecture ensures high performance, elastic scalability, and extensibility. This future-proof foundation enables Adeline to handle high-volume, real-time workloads with ease.

At Operative's AI Lab, we're pushing the boundaries of what's possible in media sales automation. Our goal is to empower sellers to focus on relationship-building and revenue generation while leveraging AI to handle the rest. If you're passionate about the intersection of AI and media technology, let's connect and redefine the future of media sales together.
#AI #MediaTech #SalesAutomation #MachineLearning #ConversationalAI Show less

Operative is teaming with Goldbach Media, a leading Swiss TV media company, to roll out Operative's next-generation AOS product to modernize and digitally transform linear media buying and optimization.

Moving Beyond the Legacy: Goldbach currently uses a legacy platform called MediaPro to manage sales workflows across linear TV and digital advertising. While effective for many years, the system has hit critical pain points around usability, scalability, costs, and vendor risk. AOS… Show more

Operative is teaming with Goldbach Media, a leading Swiss TV media company, to roll out Operative's next-generation AOS product to modernize and digitally transform linear media buying and optimization.

Moving Beyond the Legacy: Goldbach currently uses a legacy platform called MediaPro to manage sales workflows across linear TV and digital advertising. While effective for many years, the system has hit critical pain points around usability, scalability, costs, and vendor risk. AOS delivers the needed capabilities and flexibility on a future-proof platform.

A Phased Journey: The project takes a phased approach over three parts - first moving Replay Ads capabilities to AOS. Next, Goldbach will transition additional linear and cross-platform functions to AOS. Finally, the remaining finance and operations workflows are optimized within MediaPro.

Business Agility and Innovation: A key driver is enabling new ways of media buying and selling leveraging AOS's optimization, automation and integrated workflows to improve business performance. The companies are working together to deliver an innovative, yet tailored enterprise platform that provides a competitive edge for years to come.

The path will require change management and close collaboration between partners, but promises significant long-term payoff in an exciting industry undergoing massive transformation. Show less

ONTARGET FORECASTING

Utilizing experience from multiple successful pilots across BARB, Nielsen, IBOPE, and OzTam between 2016-2019

Provisioning advanced tailored feature engineering methods for metadata enrichment.
Typical (3+ years) of historical data improves forecast accuracy by 30%
Adding Content, Social Media and Emotional Resonance metadata reduces error rates by 48%

AWS based, Open APIs and Microservice Technology stack with AWS SageMaker (ML).

New big data project combining our long & established knowledge of scheduling and content data with audience measurement and user segmentation for broadcaster insights and systematic integration into our MBSs

OTT Solution for Enterprise Broadcaster Business.

Integrated campaign management system for cinema advertisers.

Providing & Supporting 3 data Science Projects to MSc Data Science Students as final studying projects.

Topics for this year:
* Short text (synopsis) analysis and advanced modeling for content learning (NLP & ML).
* Advanced vector similarity analysis and modeling (ML)

Providing and supervising 5 research projects for final MSc data science works

* Providing project work, data and guidance.
* Supervising the project execution.

Selected research Topics:
> Predicting next episode success using short term social (demand) metrics.
> SVOD Binge released content viewership evaluation and prediction and impact on traditional TV
> Forecasting TV Series syndication success
> Torrent as demand metric for content success and… Show more

Providing and supervising 5 research projects for final MSc data science works

* Providing project work, data and guidance.
* Supervising the project execution.

Selected research Topics:
> Predicting next episode success using short term social (demand) metrics.
> SVOD Binge released content viewership evaluation and prediction and impact on traditional TV
> Forecasting TV Series syndication success
> Torrent as demand metric for content success and forecasting piracy levels.
> Content Topic Scoring evaluation using Hearing Impaired subtitles.


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Support data science projects for MSc graduates (UCL, University of Salford, University of Greenwich)


MSc Submitted Project included:
> TV viewership prediction utilizing content topic scoring
> TV Viewership Analysis using Data Mining Techniques
> Segmentation of Audience Data

Using deep learning and data enrichment for predicting audiences for Entertainment and Sports channels.

Utilizing 3 years of historical viewership data.
Enrichment of Entertainment data by content metadata including topic scoring and advanced series analysis.
Enrichment of Football data by sports stats and social media metrics for competing teams

Result:
Ensemble of algorithms and models reduced error by >30% RMSE and 53% MAE

Combining our know-how of media content management data and Scheduling (Linear and No-linear Broadcast) management data with multi-sources and multi-levels of Audience Measurement data adding Audience profiling (segmentation) and a dash of social media inputs in order to masterfully predict content viewability and impact.

The project involves multiple large software companies and universities.

Business and Technical Design, Development Management and Project Management.
Integration of IBMS Acquisitions, Media and Scheduling modules into Scripps own data bus and ESearch system

Design and development of advanced scheduling features allowing multi-region broadcast of radio content via IBMS Scheduling module

Design and Development of large customization project.
Amortization Rules, Production Management module, Satellite Requisitions and Event Profiles.
CRTC Integration with IBMS Modules

Business and Technical Analysis, design and development of a VOD management system.
Integration into IBMS Acquisitions, Broadcast Rights and Finance Modules.
Delivery of product and support post successful go-live.

Design and development of National Geographic multi-region financial support system.
Complex distribution of costing and content amortization for intentional regions/countries of broadcasting.

Integrating multi-region multi-channel client content management system (PDS) bi-directionally with IBMS Content.
Including many media content enhancements to IBMS Acquisitions and Broadcast Rights management.

Advanced Amortization Methods
Enhanced Balance Sheets
Partitioning of Acquisitions and Finance modules by Channel

Major customization, integration and Data Migration in a multi-channel, multi-language, central European broadcaster